Microarray data classification by multi-information based gene scoring integrated with Gene Ontology

Vincent Shin-Mu Tseng*, Hsieh Hui Yu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Selecting informative genes is one of the most important issues for deciphering biological information hidden in gene expression data. However, due to the characteristics of microarray data with small samples and large number of genes, general feature selection methods that are not biologically relevant become questionable. In this paper, we propose a novel classification method for microarray data by integrating the multi-information based gene scoring method with biological information. Through experimental evaluation, our proposed method is shown to deliver good accuracy in classification and provide biologists with deeper insights into the relations between genes and gene function categories.

Original languageEnglish
Pages (from-to)402-416
Number of pages15
JournalInternational Journal of Data Mining and Bioinformatics
Volume5
Issue number4
DOIs
StatePublished - 1 Jul 2011

Keywords

  • GO
  • Gene expression analysis
  • Gene ontology
  • Gene scoring
  • Microarray data classification

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